Search

Your search keyword '"Zhang, Jianyou"' showing total 156 results
Start Over Author "Zhang, Jianyou"
156 results on '"Zhang, Jianyou"'

17. Recent advance in technological innovations of sugar-reduced products.

Author

Zhang, Gaopeng, Zhang, Lyu, Ahmad, Ishtiaq, Zhang, Jianyou, Zhang, Anqiang, Tang, Wei, Ding, Yuting, and Lyu, Fei

Subjects
SWEETENERS, CORONARY disease, FOOD substitutes, FOOD texture, XYLITOL, ESSENTIAL nutrients
Abstract

Sugar is crucial as an essential nutrient for humans as well as for providing texture, sweetness and so on to food. But with the rise in people's pursuit of health, it is becoming increasingly clear that excessive consumption of sugar can locate a load on the body. It has been that excessive sugar is associated with many diseases, such as dental caries, obesity, diabetes, and coronary heart disease. Therefore, researchers and industries are trying to reduce or substitute sugar in food without affecting the sensory evaluation. Substituting sugar with sweeteners is alternatively becoming the most traditional way to minimize its use. So far, the sweeteners such as stevia and xylitol have been are commercially applied. Several studies have shown that technological innovation can partially compensate for the loss in sweetness as a result of sugar reduction, such as cross-modal interactions that stimulate sweetness with aroma, nanofiltration that filters disaccharides and above, enzyme-catalyzed sugar hydrolysis, and microbial fermentation that turns sugar into sugar alcohol. This review summarizes these studies to enhance the safety and quality of sugar-reduced products, and will provide some theoretical frameworks for the food industry to reduce sugar in foods, meet consumers' needs, and promote human health. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

19. Effect of low‐voltage electrostatic field‐assisted partial freezing on large yellow croaker protein properties and metabolomic analysis during storage.

Author

Fei, Lifeng, Ma, Ze, Yue, Aodong, Cui, Pengbo, Qiu, Yue, Lyu, Fei, and Zhang, Jianyou

Subjects
LARIMICHTHYS, METABOLOMICS, AMINO acid metabolism, FLUORESCENCE spectroscopy, ELECTROSTATIC fields, MICROBIAL enzymes
Abstract

Background: Large yellow croaker is highly perishable during storage because of high protein and moisture content. The degradation of the fish is mainly attributed to microbial growth and enzyme activity, so it is important to find an efficient storage method to extend its shelf life. Methodology: This study investigated the effect of a low‐voltage electrostatic field combined with partial freezing treatment on the physicochemical properties of myofibrillar protein (MP) and metabolomic analysis of large yellow croaker during preservation. The samples in chilled storage (C), partial freezing storage (PF) and 6 kV/m low‐voltage electrostatic field partial freezing storage (LVEF‐PF) were analyzed during an 18 day storage period. Results: In comparison with the C and PF groups, LVEF‐PF delayed the oxidation of MP by inhibiting the formation of carbonyl groups (2.25 nmol/mg pro), and maintaining higher sulfhydryl content (29.73 nmol/mg pro). Fourier transform infrared (FTIR) spectroscopy and fluorescence spectroscopy analysis also demonstrated that the LVEF‐PF treatment maintained the stability of the protein structure by increasing the a‐helix ratio (19.88%) and reducing the random coil ratio (17.83%). Scanning electron microscopy showed that, compared with the LVEF‐PF group, there was more degeneration and aggregation of MP in the C and PF groups after 18 days' storage. The results of untargeted metabolomic analysis showed that 415 kinds of differential metabolites were identified after storage, and the difference levels of differential metabolites were least between the samples treated with LVEF‐PF stored on the ninth day and the fresh samples. The main differential metabolic pathways during storage were amino acid metabolism and lipid metabolism. Conclusion: The LVEF‐PF treatment could maintain the stability of myofibrillar protein in large yellow croaker during storage. These results showed a potential application of the LVEF‐PF method for aquatic product preservation. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

25. Binary Grasshopper Optimization Based Feature Selection for Intrusion Detection System Using Feed Forward Neural Network Classifier

Author

Thirumalairaj A., S. Sehgal Satbir, S. Chohan Jasgurpreet, Gupta Mansi, Chaturvedi Rachna, Nath Alok, Lyu Fei, Sarma Ganti Subrahmanya, Chen Lifan, Wang Meizhen, Mittal Karan, Khan Ajmal, Zhang Jianyou, Sharma Adity, Chernyuk Daria, Arora Daisy, Popugaeva Elena, Li Caili, Bezprozvanny Ilya, Kumar Maurya Rajesh, Agarwal Vikas, Singh Harshit, Zhou Hong, Wang Zhen, Kumar Raman, Qiu Xiaoxiao, Jeyakarthic M., Mishra Ravi, Mishra Vijay, Lu Shanfa, Hashim Zia, Ding Yuting, Zhou Xuxia, and Chen Zhiming

Subjects
General Computer Science, Computer science, business.industry, Binary number, Feedforward neural network, Pattern recognition, Feature selection, Artificial intelligence, Intrusion detection system, business, Classifier (UML)
Abstract

Background: Due to the advanced improvement in internet and network technologies, significant number of intrusions and attacks takes place. An intrusion detection system (IDS) is employed to prevent distinct attacks. Several machine learning approaches has been presented for the classification of IDS. But, IDS suffer from the curse of dimensionality that results to increased complexity and decreased resource exploitation. Consequently, it becomes necessary that significant features of data must be investigated by the use of IDS for reducing the dimensionality. Aim: In this article, a new feature selection (FS) based classification system is presented which carries out the FS and classification processes. Methods: Here, the binary variants of the Grasshopper Optimization Algorithm called BGOA is applied as a FS model. The significant features are integrated using an effective model to extract the useful ones and discard the useless features. The chosen features are given to the feed forward neural network (FFNN) model to train and test the KDD99 dataset. Results: The validation of the presented model takes place using a benchmark KDD Cup 1999 dataset. By the inclusion of FS process, the classifier results gets increased by attaining FPR of 0.43, FNR of 0.45, sensitivity of 99.55, specificity of 99.57, accuracy of 99.56, Fscore of 99.59 and kappa value of 99.11. Conclusion: The experimental outcome ensured the superior performance of the presented model compared to diverse models under several aspects and is found to be an appropriate tool for detecting intrusions.

Published
2021

29. Interactions of Fish Proteins and Volatile Flavor Compounds: Mechanisms, Affecting Factors and Analytical Methods

Author

Chen Zhiming, Chen Lifan, Zhang Jianyou, Zhou Xuxia, Lyu Fei, Wang Zhen, and Ding Yuting

Subjects
Chemistry, Organic Chemistry, Volatile flavor, Food science, Fish Proteins
Abstract

The removal of volatile compounds with unfavorable fishy odor from fish has attracted considerable research attention especially in surimi production industry. The binding of these volatile compounds by fish proteins are reported to affect the deodorization of fishy odor. To remove the protein- bound fishy substances effectively, the mechanisms underlying the interaction between proteins and flavor substances and methods that can extract and analyze the aromatic substances have been extensively studied. This paper briefly reviews the typical fishy compounds and the combination modes and mechanisms of fish proteins with these compounds. Moreover, factors affecting the interactions including protein conformation and solution conditions are discussed in detail.

Published
2021

46. Evaluation of whitening efficacy and safety of the water extract from bamboo shavings

Author

Lu Baiyi, Zhang Ying, Zhang Jianyou, Gong Jinyan, and Wu Xiaoqin

Subjects
Pharmacology, Bamboo, integumentary system, Hydroquinone, Tyrosinase, education, Arbutin, Pharmaceutical Science, Plant Science, Melanin, chemistry.chemical_compound, Skin irritation, Complementary and alternative medicine, chemistry, Drug Discovery, Botany, Food science, Cytotoxicity, IC50
Abstract

This aim of this study was to evaluate the whitening efficacy of the water extract from bamboo shavings (WEBS) in malignant melanoma cells (B-16) of mice. The safety of WEBS was evaluated by the acute oral toxicity test, the repeated skin irritation test and the acute eye irritation test was also evaluated. WEBS showed strong inhibitory effects against the activity of tyrosinase in B-16 cells in a dose dependent manner, and was more potent than arbutin. The melanin content was significantly inhibited by WEBS and the cytotoxicity of WEBS was lower than that of arbutin and hydroquinone. WEBS inhibited mushroom tyrosinase and the maximum was 65.05% at 16 mg/ml with an IC50 of 6 mg/ml. The LD50 was larger than 5000 mg/kg body weight and WEBS was found to be non-toxic and non-irritating. Key words: Water extract of bamboo shavings, whitening effect, B-16 melanoma cell, safety evaluation.

Published
2014

Catalog

Books, media, physical & digital resources
See catalog results